CN104867037B - A kind of data processing method and device of Figure Characteristics - Google Patents
A kind of data processing method and device of Figure Characteristics Download PDFInfo
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- CN104867037B CN104867037B CN201510289785.3A CN201510289785A CN104867037B CN 104867037 B CN104867037 B CN 104867037B CN 201510289785 A CN201510289785 A CN 201510289785A CN 104867037 B CN104867037 B CN 104867037B
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Abstract
The embodiment of the invention provides a kind of data processing method of Figure Characteristics and devices.This method comprises: obtaining, there are the features of the user of transaction relationship with target object, carry out statistical disposition according to the feature of acquired user, and establish the Figure Characteristics of target object, are finally shown the Figure Characteristics of target object by application interface.The embodiment of the present invention is by using above-mentioned technical proposal, target object is portrayed with anthropomorphic angle, the Figure Characteristics image established is succinct and rich in specific aim, user can match Figure Characteristics with own actual situation, easily and accurately select suitable commodity, shopping-time is saved, the shopping experience of user can be effectively promoted.
Description
Technical field
The present embodiments relate to electric business platform field more particularly to the data processing methods and dress of a kind of Figure Characteristics
It sets.
Background technique
With the fast development of e-commerce, more and more users' selection is done shopping in electric business platform.On electric business platform
Retail shop, brand and type of merchandize are various, and user would generally be with reference to product features, the Sales Volume of Commodity, commodity valence that electric business platform provides
Lattice, number of reviews or comment content etc. select to make purchase.
However, the buyer of same commodity usually has the difference of gender, age, occupation etc., user is referring to commodity
Sales volume, number of reviews or comment content can not accurately judge the commodity if appropriate for oneself, and comment on content in as
Above-mentioned difference and exist largely without reference to the content of value, the great effort of user can be expended.In addition, existing product features
Usually by the background work personnel of businessman according to commodity details understanding and the subjective factors such as working experience added manually
Add, or the main parameter of commodity is only set out.The mode of above-mentioned backstage addition product features has subjectivity and fixation
Property, and it is cumbersome, the product features added in this way can not make whether user fast and accurately understands the commodity
It is suitble to oneself.
In short, to be unable to satisfy user quick for commodity provided by existing electric business platform, brand and the characteristic information of retail shop
The demand for accurately selecting suitable commercial product, be easy to cause shopping experience bad.
Summary of the invention
The purpose of the present invention is to propose to a kind of data processing method of Figure Characteristics and devices, can show quotient from trend user
Product, brand or the Figure Characteristics of retail shop, with solve merchandise news provided by electric business because data volume is huge, be lack of pertinence due to lead
It applies family the problem of can not rapidly and accurately selecting suitable commercial product.
On the one hand, the embodiment of the invention provides a kind of data processing methods of Figure Characteristics, comprising:
There are the features of the user of transaction relationship with target object for acquisition；
Statistical disposition is carried out according to the feature of the user, establishes the Figure Characteristics of the target object；
The Figure Characteristics of the target object are shown by application interface.
On the other hand, the embodiment of the invention provides a kind of data processing equipments of Figure Characteristics, comprising:
User characteristics obtain module, and for obtaining, there are the features of the user of transaction relationship with target object；
Figure Characteristics establish module, for carrying out statistical disposition according to the feature of the user, establish the target object
Figure Characteristics；
Figure Characteristics display module, for being shown the Figure Characteristics of the target object by application interface.
The data processing method of the Figure Characteristics provided in the embodiment of the present invention, there are transaction relationships with target object for acquisition
User feature, statistical disposition is carried out according to the feature of acquired user, and establishes the Figure Characteristics of target object, finally
The Figure Characteristics of target object are shown by application interface.By using above-mentioned technical proposal, with anthropomorphic angle pair
Target object is portrayed, and the Figure Characteristics image established is succinct and rich in specific aim, and user can be by Figure Characteristics and itself
Actual conditions are matched, and suitable commodity are easily and accurately selected, and are saved shopping-time, can effectively be promoted the shopping body of user
It tests.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the data processing method for Figure Characteristics that the embodiment of the present invention one provides；
Fig. 2 is a kind of flow diagram of the data processing method of Figure Characteristics provided by Embodiment 2 of the present invention；
Fig. 3 is a kind of structural block diagram of the data processing equipment for Figure Characteristics that the embodiment of the present invention three provides；
Fig. 4 is a kind of flow diagram of the data processing method for Figure Characteristics that the embodiment of the present invention four provides；
Fig. 5 is the processing flow schematic diagram that user characteristics are screened in the embodiment of the present invention four；
Fig. 6 is a kind of simple flow schematic diagram of the data processing method for Figure Characteristics that the embodiment of the present invention four provides.
Specific embodiment
To further illustrate the technical scheme of the present invention below with reference to the accompanying drawings and specific embodiments.It is understood that
It is that specific embodiment described herein is used only for explaining the present invention rather than limiting the invention.It further needs exist for illustrating
, only the parts related to the present invention are shown for ease of description, in attached drawing rather than entire infrastructure.
Embodiment one
Fig. 1 is a kind of flow diagram of the data processing method for Figure Characteristics that the embodiment of the present invention one provides, the party
Method can be executed by the data processing equipment of the Figure Characteristics in the embodiment of the present invention.As shown in Figure 1, this method comprises:
Step 101, there are the features of the user of transaction relationship with target object for acquisition.
In the present embodiment, the target object concretely commodity, brand or retail shop etc..Specifically, working as the target
When object is commodity, the commodity refer specifically to stock-keeping unit (Stock Keeping Unit, SKU) (or SKU granularity), i.e. commodity
The minimum unit of inventory.Such as: iphone6 has a variety of SKU such as white 16G, gold 16G, white 64G, gold 64G；Certain T-shirt
There are a variety of SKU such as white S code, black S code, white M code, black M code.When selecting commodity on the shopping interface of electric business, user
After needing to be determined all specifications parameters to be selected, a SKU, i.e. commodity described in the present embodiment are just had selected.
Illustratively, user's concrete meaning there are commutative relation can are as follows: when target object is commodity, can refer to purchase
Buy or pay close attention to the user of the commodity；When target object is brand, the user for buying or paying close attention to commodity under the brand can refer to；Work as mesh
When mark object is retail shop, the user for buying or paying close attention to commodity in the retail shop can refer to.Wherein, the purchase may include having subscribed,
The behaviors such as place an order, received；The concern, which may include collection, shopping cart is added, subscribe to price reduction reminds, into item detail page
Equal behaviors.
Illustratively, the feature of the user may include gender, age or the age bracket of user, education degree, income or
Take in section, place city, hobby, the quantity for buying certain commodity and number etc..
Preferably, in this step, it obtains with target object there are after the feature of the user of transaction relationship, it can also be to institute
The data of acquisition are pre-processed, i.e., are targetedly retained and given up according to preset screening conditions.In electric business platform
The commodity of SKU dimension are numerous, due to some commodity for not having sales volume or not being concerned because user participate in it is less and other reasons, can
Sample data for establishing Figure Characteristics is insufficient, so can selectively be given up.Illustratively, in three-level classified commodity
In, give up undercarriage commodity and presell commodity first, retains commodity on sale；In commodity on sale, give up no sales volume commodity, retains
There are sales volume commodity；Obtained in having sales volume commodity sales volume be greater than corresponding to the commodity of average sales volume with there are the use of transaction relationship
The feature at family；For there is the sales volume in sales volume commodity to be less than the commodity of average sales volume, attention rate can be given up and be less than average attention rate
Commodity, and select to obtain attention rate be greater than corresponding to the commodity of average attention rate with there are the spies of the user of transaction relationship
Sign.By carrying out above-mentioned screening, the data got can be made more representative, by subsequent step to these data into
The processing of one step, the Figure Characteristics established are also more accurately and rich in specific aim.
Step 102 carries out statistical disposition according to the feature of user, establishes the Figure Characteristics of target object.
In this step, feature can be called to select function, statistical disposition is carried out to the feature of user, establish target object
Figure Characteristics.The feature select function specifically and may include but be not limited to such as summing function in statistics, function of averaging,
The composite function of maximizing function and any one function such as seek mode function or any number of functions.
Illustratively, the mean value computation that the feature of user can be carried out to attribute value according to dimension, is higher than mean value for attribute value
Figure Characteristics of the feature as target object.Wherein, the dimension concretely attribute classification, such as gender, age or age
Section, education degree, income or income section, place city, hobby, the quantity for buying certain commodity and number etc.；Attribute
The attribute that concretely may include in each attribute classification, such as the attribute of gender can be " male " or " female ", age bracket
Attribute can be " 20 years old or less ", " 20-30 years old ", " 30-40 years old ", " 40-50 years old " and " 50 years old or more " etc., the category of education degree
Property can be " training and following ", " undergraduate course ", " master or more " etc..Attribute value specifically can refer to the corresponding quantity of attribute, such as people
Number.The average value of all properties value in each attributive classification is sought, then attribute value is higher than the feature of mean value as target object
Figure Characteristics, correspondingly, feature involved by the above method selects function includes:
Wherein, Ai is attribute value, and N is attribute number, and P is average value.
After the attribute value average value for calculating each attributive classification according to above-mentioned formula, by each attribute value and the average value
It is compared, will be above Figure Characteristics of the attribute value as target object of the average value.
Table 1 below gives being 20151111111 according to above method picking commodities number, (or SKU is XX type M indigo plant
Color) commodity Figure Characteristics detailed process.
Table 1
As shown in table 1, the data for being passed to (acquisition) may include goods number or SKU, attribute value, include meter in calculating process
Attribute value sum and statistical attribute number are calculated, average value is calculated by attribute value sum and attribute number, further according to each attribute
The comparison result backout feature of value and average value selects conclusion.For example, the male's number for buying the commodity is 18 people, women number
For 12 people, sum is 30 people, and attribute number is 2 (male and female), and calculating average value is 15 people, is more than because male buys number
Average value, and women buys number subaverage, so " male " to be picked as to a Figure Characteristics of the commodity.Similarly, by
Upper table can be seen that the Figure Characteristics of the commodity include " male ", " undergraduate course ", " B ", " Beijing " and " Shanghai ", i.e. the commodity are more suitable
It is B for undergraduate course educational background, income section, lives in the male user in Beijing or Shanghai.Table 1 illustrates only several representational
Attributive classification and attribute can be configured according to the actual situation in the concrete application embodiment of the present invention.
The Figure Characteristics of target object are shown by step 103 by application interface.
In this step, the Figure Characteristics for the target object established in step 102 are shown by application interface.
The application interface concretely shows the interface of Figure Characteristics to user, can also be electric business internal work personnel for obtaining picture
As the internal system application interface etc. of feature, data are provided for commodity operation and management and precision marketing etc. and are supported, be user
Preferably service is provided.Specifically, when the target object is commodity, it can be in the items list of electric business shopping page or quotient
The Figure Characteristics that commodity are shown in product details, facilitate user easily to select suitable commodity referring to commodity Figure Characteristics；Work as institute
State target object be brand when, brand Figure Characteristics can be shown in the list of brands of electric business shopping page or in brand details,
Facilitate user easily to select the brand for being suitble to oneself referring to brand Figure Characteristics, and then selects the commodity under the brand；Work as institute
State target object be retail shop when, retail shop's Figure Characteristics can be shown in retail shop's list of electric business shopping page or in retail shop's details,
Facilitate user easily to select the retail shop admired referring to retail shop's Figure Characteristics, and then selects the quotient in the retail shop into the retail shop
Product.Preferably, Figure Characteristics can be established respectively to commodity, brand and retail shop and application interface is shown, facilitate user according to
Itself habit selection checks corresponding Figure Characteristics to carry out choosing for commodity.
The data processing method for the Figure Characteristics that the embodiment of the present invention one provides, there are transaction relationships with target object for acquisition
User feature, statistical disposition is carried out according to the feature of acquired user, and establishes the Figure Characteristics of target object, finally
The Figure Characteristics of target object are shown by application interface.By using above-mentioned technical proposal, the portrait established is special
Sign image is succinct and rich in specific aim, and Figure Characteristics can be matched with own actual situation, easily and accurately be selected by user
Suitable commodity save shopping-time, can effectively promote the shopping experience of user.
Embodiment two
Fig. 2 is a kind of flow diagram of the data processing method of Figure Characteristics provided by Embodiment 2 of the present invention, this reality
It applies example to optimize based on above-described embodiment, as shown in Fig. 2, method provided in this embodiment includes the following steps:
Step 201, the feature for obtaining purchase or paying close attention to the user of commodity.
Step 202 carries out statistical disposition according to the feature of user, establishes the Figure Characteristics of commodity.
Illustratively, the mean value computation that the feature of user can be carried out to attribute value according to dimension, is higher than mean value for attribute value
Figure Characteristics of the feature as commodity.
Step 203, the Figure Characteristics for obtaining commodity carry out statistical disposition according to the Figure Characteristics of commodity, establish brand
Figure Characteristics.
Illustratively, after the Figure Characteristics for establishing commodity in step 202, can obtain under brand all is established
The commodity of Figure Characteristics carry out statistical disposition, and the Figure Characteristics of commodity can specifically be carried out to the mean value meter of attribute value according to dimension
It calculates, attribute value is higher than the feature of mean value as the Figure Characteristics of brand.For example, 200 kinds of commodity are shared under certain brand, wherein
There are 180 kinds of commodity to establish Figure Characteristics, for this attribute classification of gender, there are the Figure Characteristics of 120 commodity to be
" female ", and the Figure Characteristics of remaining 60 commodity are " male ", that is, the attribute value of attribute " female " is 120, and attribute " male "
Attribute value be 60, attribute value sum be 120, average value 90, because attribute " female " attribute value be greater than mean value, then will " female " work
For a Figure Characteristics of the brand, illustrate that the product women buyer under the brand is more.
Step 204, the Figure Characteristics for obtaining commodity and/or brand, unite according to the Figure Characteristics of commodity and/or brand
Meter processing, establishes the Figure Characteristics of retail shop.
Illustratively, a retail shop there may be multi-brand is managed simultaneously, as moved class, it will usually pass through simultaneously
Multiple brands are sought, for this kind of retail shops, the Figure Characteristics that can obtain all brands in retail shop carry out statistical disposition, specifically may be used
Attribute value is higher than the feature of mean value as retail shop by the mean value computation that the Figure Characteristics of brand are carried out to attribute value according to dimension
Figure Characteristics.And a retail shop may also only manage the commodity in a small amount of brand (brand shop of such as certain brand) or retail shop
There is no specific brand (such as hand work retail shop), for this kind of retail shops, can obtain in retail shop all establishes picture
As the commodity progress statistical disposition of feature, the Figure Characteristics of commodity can specifically be carried out to the mean value computation of attribute value according to dimension,
Attribute value is higher than the feature of mean value as the Figure Characteristics of retail shop.
Certainly, for the retail shop for managing multiple brands simultaneously, the Figure Characteristics of commodity and brand can also be obtained simultaneously
And statistical disposition is carried out, so that the data sample for statistical disposition is more comprehensive, statistical result is more accurate.
Commodity, brand and the Figure Characteristics of retail shop are passed through corresponding application interface respectively and are shown by step 205.
The data processing method of Figure Characteristics provided by Embodiment 2 of the present invention establishes commodity, brand and retail shop respectively
Figure Characteristics, and be shown respectively by corresponding application interface.This method is with anthropomorphic angle to commodity, brand and quotient
The portrait of paving is portrayed, and the Figure Characteristics image established is succinct and rich in specific aim, and user can be by Figure Characteristics and itself
Actual conditions are matched, and suitable retail shop, brand and commodity are easily and accurately selected, and are saved shopping-time, can effectively be promoted
The shopping experience of user.
Embodiment three
Fig. 3 is a kind of structural block diagram of the data processing equipment for Figure Characteristics that the embodiment of the present invention three provides, the device
Figure Characteristics data can be handled by executing the data processing method of the Figure Characteristics in the embodiment of the present invention.As shown in figure 3,
The device includes: that user characteristics obtain module 301, and for obtaining, there are the features of the user of transaction relationship with target object；It draws
As feature establishes module 302, for carrying out statistical disposition according to the feature of user, the Figure Characteristics of target object are established；Portrait
Feature display module 303, for being shown the Figure Characteristics of target object by application interface.
The data processing equipment for the Figure Characteristics that the embodiment of the present invention three provides obtains the acquisition of module 301 and mesh by feature
Marking object, there are the features of the user of transaction relationship, then establish module 302 by Figure Characteristics and counted according to the feature of user
Processing, establishes the Figure Characteristics of target object, is finally passed through the Figure Characteristics of target object by Figure Characteristics display module 303
Application interface is shown, and the Figure Characteristics image established is succinct and rich in specific aim, and user can be by Figure Characteristics and itself
Actual conditions are matched, and suitable commodity are easily and accurately selected, and are saved shopping-time, can effectively be promoted the shopping body of user
It tests.
On the basis of the above embodiments, the Figure Characteristics are established module and specifically be can also be used in: feature being called to select letter
The feature of several couples of users carries out statistical disposition, establishes the Figure Characteristics of target object.
On the basis of the above embodiments, the Figure Characteristics are established module and specifically be can also be used in: by the spy of the user
Sign carries out the mean value computation of attribute value according to dimension, and the feature that attribute value is higher than mean value is special as the portrait of the target object
Sign.
On the basis of the above embodiments, the user characteristics obtain module can include: commodity user characteristics acquiring unit,
For using commodity as target object, obtaining purchase or paying close attention to the feature of the user of the commodity.
On the basis of the above embodiments, the user characteristics, which obtain module, may also include that brand or retail shop's user characteristics
Acquiring unit, for obtaining purchase or paying close attention to commodity or the retail shop under the brand using brand or retail shop as target object
The feature of the user of middle commodity.
On the basis of the above embodiments, the Figure Characteristics establish module can include: and commodity Figure Characteristics establish unit,
For carrying out statistical disposition according to the feature of the user, the Figure Characteristics of the commodity are established；Brand Figure Characteristics are established single
Member carries out statistical disposition according to the Figure Characteristics of the commodity, establishes the picture of brand for obtaining the Figure Characteristics of the commodity
As feature；Retail shop's Figure Characteristics establish unit, for obtaining the Figure Characteristics of the commodity and/or brand, according to the commodity
And/or the Figure Characteristics of brand carry out statistical disposition, establish the Figure Characteristics of retail shop.
Example IV
Fig. 4 is a kind of flow diagram of the data processing method for Figure Characteristics that the embodiment of the present invention four provides.Such as Fig. 4
It is shown, this method may include data preparation stage, commodity portrait portray the stage, feature Choosing module processing stage, brand portrait
Portray the stage, shop portrait portrays stage and application module processing stage.
It may include data integration and data prediction in data preparation stage.Wherein, data integration step mainly obtains
The feature of the user of purchase or concern commodity (alternatively referred to as user draws a portrait)；Data prediction step is mainly to acquired user
Feature is screened, and Fig. 5 is the processing flow schematic diagram that user characteristics are screened in the embodiment of the present invention four, as shown in figure 5, having
The related data of the commodity of " X " label will be rejected, and the related data of the commodity with smiling face will be drawn with incoming commodity
As portraying the attribute value statistical module in the stage.
The stage is portrayed in commodity portrait, the goods number and user characteristics number that will acquire by attribute value statistical module therein
Attribute value in is passed in feature Choosing module, and progress attribute value summation, attribute number statistics, mean value computation, feature are selected
And etc. after, will be greater than attribute corresponding to the attribute value of mean value as keeping characteristics, and return to commodity portrait portray the stage
In attribute value statistical module, the keeping characteristics are the Figure Characteristics of commodity.
The stage is portrayed in brand portrait, the Figure Characteristics of commodity are obtained by attribute value statistical module therein, then by commodity
The corresponding attribute value of Figure Characteristics of number and commodity is passed in feature Choosing module, carries out attribute value summation, attribute number system
Meter, mean value computation, feature select and etc. after, will be greater than attribute corresponding to the attribute value of mean value as keeping characteristics, and return
The attribute value statistical module in the stage is portrayed back to brand portrait, the keeping characteristics are the Figure Characteristics of brand.
In shop, portrait portrays the stage, particularly may be divided into two parts: portraying the portrait in single-item board shop, and to multi-brand
The portrait in shop is portrayed.The portrait in single-item board shop is portrayed, commodity can be obtained by single-item board shop attribute value statistical module
Figure Characteristics, then by the corresponding attribute value of the Figure Characteristics of goods number and commodity be passed to feature Choosing module in, belonged to
The summation of property value, attribute number statistics, mean value computation, feature select and etc. after, will be greater than category corresponding to the attribute value of mean value
Property returns to single-item board shop attribute value statistical module as keeping characteristics, and the keeping characteristics are single-item board shop
Figure Characteristics.The portrait in multi-brand shop is portrayed, multiple brands can be obtained by multi-brand shop attribute value statistical module
Figure Characteristics, then the corresponding attribute value of the Figure Characteristics of goods number and brand is passed in feature Choosing module, carry out attribute
Value summation, attribute number statistics, mean value computation, feature select and etc. after, will be greater than attribute corresponding to the attribute value of mean value
As keeping characteristics, and multi-brand shop attribute value statistical module is returned to, the keeping characteristics are the picture in multi-brand shop
As feature.
Finally, the attribute value statistical module in each stage draws a portrait the commodity portrayed, brand portrait and shop portrait are distinguished
It is passed to corresponding application interface.
Fig. 6 is a kind of simple flow schematic diagram of the data processing method for Figure Characteristics that the embodiment of the present invention four provides.
In order to make it easy to understand, the simple flow schematic diagram and above-mentioned text in combinable Fig. 6 understand the technical solution in the present embodiment.
A kind of data processing method for Figure Characteristics that the embodiment of the present invention four provides, carries out in conjunction with specific flow chart
Illustrate, establishes commodity, brand and the Figure Characteristics in shop respectively, and be shown respectively by corresponding application interface.It should
Method portrays commodity, brand and the portrait in shop with anthropomorphic angle, and the Figure Characteristics image established is succinct and rich
Targetedly, user can match Figure Characteristics with own actual situation, easily and accurately select suitable retail shop, brand
And commodity, shopping-time is saved, the shopping experience of user can be effectively promoted.
Note that the above is only a better embodiment of the present invention and the applied technical principle.It will be appreciated by those skilled in the art that
The invention is not limited to the specific embodiments described herein, be able to carry out for a person skilled in the art it is various it is apparent variation,
It readjusts and substitutes without departing from protection scope of the present invention.Therefore, although being carried out by above embodiments to the present invention
It is described in further detail, but the present invention is not limited to the above embodiments only, without departing from the inventive concept, also
It may include more other equivalent embodiments, and the scope of the invention is determined by the scope of the appended claims.
Claims (8)
1. a kind of data processing method of Figure Characteristics characterized by comprising
There are the features of the user of transaction relationship with target object for acquisition；
It calls feature to select function and statistical disposition is carried out to the feature of the user, establish the Figure Characteristics of the target object；
The Figure Characteristics of the target object are shown by application interface；
Wherein, it calls feature to select function and statistical disposition is carried out to the feature of the user, establish the portrait of the target object
Feature includes:
Attribute value is higher than the feature of mean value as institute by the mean value computation that the feature of the user is carried out to attribute value according to dimension
State the Figure Characteristics of target object.
2. the method according to claim 1, wherein obtaining, there are the spies of the user of transaction relationship with target object
Sign includes:
Using commodity as target object, obtains purchase or pay close attention to the feature of the user of the commodity.
3. according to the method described in claim 2, it is characterized in that, obtain there are the spies of the user of transaction relationship with target object
Sign includes:
Using brand or retail shop as target object, obtains purchase or pay close attention to the use of commodity in commodity under the brand or the retail shop
The feature at family.
4. according to the method described in claim 2, it is characterized in that, if the target object is commodity, according to the use
The feature at family carries out statistical disposition, establishes after the Figure Characteristics of the commodity, further includes:
The Figure Characteristics for obtaining the commodity carry out statistical disposition according to the Figure Characteristics of the commodity, establish the portrait of brand
Feature；
The Figure Characteristics for obtaining the commodity and/or brand carry out Statistics Division according to the commodity and/or the Figure Characteristics of brand
Reason, establishes the Figure Characteristics of retail shop.
5. a kind of data processing equipment of Figure Characteristics characterized by comprising
User characteristics obtain module, and for obtaining, there are the features of the user of transaction relationship with target object；
Figure Characteristics establish module, carry out statistical disposition to the feature of the user for calling feature to select function, establish institute
State the Figure Characteristics of target object；
Figure Characteristics display module, for being shown the Figure Characteristics of the target object by application interface；
Wherein, the Figure Characteristics are established module and are specifically used for: the feature of the user is carried out the equal of attribute value according to dimension
Value calculates, and attribute value is higher than the feature of mean value as the Figure Characteristics of the target object.
6. device according to claim 5, which is characterized in that the user characteristics obtain module and include:
Commodity user characteristics acquiring unit, for using commodity as target object, obtaining purchase or paying close attention to the user of the commodity
Feature.
7. device according to claim 6, which is characterized in that the user characteristics obtain module further include:
Brand or retail shop's user characteristics acquiring unit, for obtaining purchase or concern institute using brand or retail shop as target object
State the feature of the user of commodity in commodity under brand or the retail shop.
8. device according to claim 6, which is characterized in that the Figure Characteristics establish module and include:
Commodity Figure Characteristics establish unit, for carrying out statistical disposition according to the feature of the user, establish the picture of the commodity
As feature；
Brand Figure Characteristics establish unit, for obtaining the Figure Characteristics of the commodity, according to the Figure Characteristics of the commodity into
The Figure Characteristics of brand are established in row statistical disposition；
Retail shop's Figure Characteristics establish unit, for obtaining the Figure Characteristics of the commodity and/or brand, according to the commodity and/
Or the Figure Characteristics of brand carry out statistical disposition, establish the Figure Characteristics of retail shop.
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| CN201510289785.3A CN104867037B (en) | 2015-05-29 | 2015-05-29 | A kind of data processing method and device of Figure Characteristics |
| HK15112533.2A HK1212073A1 (en) | 2015-05-29 | 2015-12-18 | Data-processing method and device for image feature |
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| CN201510289785.3A CN104867037B (en) | 2015-05-29 | 2015-05-29 | A kind of data processing method and device of Figure Characteristics |
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| CN105893406A (en) * | 2015-11-12 | 2016-08-24 | 乐视云计算有限公司 | Group user profiling method and system |
| CN106056407A (en) * | 2016-06-03 | 2016-10-26 | 北京网智天元科技股份有限公司 | Online banking user portrait drawing method and equipment based on user behavior analysis |
| CN108090688B (en) * | 2017-12-29 | 2021-03-26 | 重庆勤鸟圈科技有限公司 | Intelligent fitness management system |
| CN110442794B (en) * | 2019-08-12 | 2023-03-31 | 上海时廊人工智能科技有限公司 | Construction method of analyst portrait system |
| CN110928893B (en) * | 2019-11-18 | 2022-10-21 | 中国建设银行股份有限公司 | Label query method, device, equipment and storage medium |
| CN111581296B (en) * | 2020-04-02 | 2022-08-16 | 深圳壹账通智能科技有限公司 | Data correlation analysis method and device, computer system and readable storage medium |
| CN112990973B (en) * | 2021-03-22 | 2023-06-30 | 山东顺能网络科技有限公司 | Online shop portrait construction method and system |
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2015
- 2015-05-29 CN CN201510289785.3A patent/CN104867037B/en active Active
- 2015-12-18 HK HK15112533.2A patent/HK1212073A1/en unknown
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1363898A (en) * | 2000-12-28 | 2002-08-14 | 富士通株式会社 | Purchasing method and systems on line |
| CN102104613A (en) * | 2009-12-18 | 2011-06-22 | 北京闻言科技有限公司 | Technology for realizing recommendation of personalized commodities at mobile phone client |
| CN105869001A (en) * | 2015-01-19 | 2016-08-17 | 苏宁云商集团股份有限公司 | Customized product recommendation guiding method and system |
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| HK1212073A1 (en) | 2016-06-03 |
| CN104867037A (en) | 2015-08-26 |
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